Search Results (1,272)

Introduction: Gastrointestinal stromal tumors (GISTs) are primarily driven by mutations in KIT (KIT proto-oncogene receptor tyrosine kinase) or PDGFRA (platelet-derived growth factor receptor alpha), but resistance to tyrosine kinase inhibitors (TKIs) such as imatinib remains a major clinical challenge. Alterations in fibroblast growth factor receptor 2 (FGFR2), although rare, are emerging as important contributors to tumor progression and drug resistance. This review evaluates the molecular mechanisms, expression profiles, detection methods, and therapeutic implications of FGFR2 in GIST. Methods: We searched PubMed, Web of Science, Google Scholar, and ClinicalTrials.gov for studies published between January 2010 and June 2025, using combinations of keywords related to FGFR2, gastrointestinal stromal tumor, resistance mechanisms, gene fusion, amplification, polymorphisms, and targeted therapy. Eligible studies were critically assessed to distinguish GIST-specific data from evidence extrapolated from other cancers. Results:FGFR2 is expressed in multiple normal tissues and at variable levels in mesenchymal-derived tumors, including GIST. Its alterations occur in approximately 1–2% of GIST cases, most commonly as gene fusions (e.g., FGFR2::TACC2, <1%) or amplifications (1–2%); point mutations and clinically significant polymorphisms are extremely rare. These alterations activate the MAPK/ERK and PI3K/AKT pathways, contribute to bypass signaling, and enhance DNA damage repair, thereby promoting TKI resistance. Beyond mutations, mechanisms such as amplification, ligand overexpression, and microenvironmental interactions also play roles. FGFR2 alterations appear mutually exclusive with KIT/PDGFRA mutations but occasional co-occurrence has been reported. Current clinical evidence is largely limited to small cohorts, basket trials, or case reports. Conclusions:FGFR2 is an emerging oncogenic driver and biomarker of resistance in a rare subset of GISTs. Although direct evidence remains limited, particularly regarding DNA repair and polymorphisms, FGFR2-targeted therapies (e.g., erdafitinib, pemigatinib) show potential, especially in combination with TKIs or DNA-damaging agents. Future research should prioritize GIST-specific clinical trials, the development of FGFR2-driven models, and standardized molecular diagnostics to validate FGFR2 as a therapeutic target. Full article

Dendrobium officinale (Orchidaceae) is a commonly used medicinal and edible herb. Although its anti-ageing properties have been demonstrated, the underlying mechanisms remain unclear. We employed network pharmacology and molecular biology techniques to systematically explore its anti-ageing mechanisms. An ageing model was established using D-galactose-induced Kunming mice. D. officinale significantly ameliorated ageing-related symptoms, including behavioural impairment and organ index reduction. It enhanced antioxidant capacity by increasing serum T-AOC levels and restoring renal activities of key antioxidant enzymes (SOD, GSH-Px, CAT) while reducing MDA; it suppressed serum TNF-α levels, indicating anti-inflammatory effects. Histopathological examination revealed that D. officinale alleviated D-galactose-induced renal damage, including tubular cell swelling and glomerular capsule widening. Network pharmacology identified 8 core active compounds (e.g., 5,7-dihydroxyflavone, naringenin) and 10 key targets (e.g., HSP90AA1, EGFR, MAPK3). KEGG analysis highlighted pathways including neuroactive ligand–receptor interaction, cAMP signalling, and calcium signalling. Molecular docking confirmed strong binding affinities between core compounds and key targets. Western blotting and immunohistochemistry validated that D. officinale upregulated EGFR, HSP90AA1, ERK, and GAPDH expression in renal tissues. In summary, D. officinale exerts anti-ageing effects by modulating oxidative stress, suppressing inflammation, and regulating multiple signalling pathways. Our findings provide a scientific rationale for its application in anti-ageing interventions. Full article

Immunogenic cell death (ICD) is a specialized form of cell death that triggers antitumor immune responses. In tumors, ICD promotes the release of tumor-associated and tumor-specific antigens, thereby reshaping the immune microenvironment, restoring antitumor immunity, and facilitating tumor eradication. However, the regulatory mechanisms of ICD and its immunological effects vary across tumor types, and a comprehensive understanding remains limited. We systematically analyzed the expression of 34 ICD-related regulatory genes across 33 tumor types. Differential expression at the RNA, copy number variation (CNV), and DNA methylation levels was assessed in relation to clinical features. Associations between patient survival and RNA expression, CNVs, single-nucleotide variations (SNVs), and methylation were evaluated. Patients were stratified into immunological subtypes and further divided into high- and low-risk groups based on optimal prognostic models built using a machine learning framework. We explored the relationships between ICD-related genes and immune cell infiltration, stemness, heterogeneity, immune scores, immune checkpoint and regulatory genes, and subtype-specific expression patterns. Moreover, we examined the influence of immunotherapy and anticancer immune responses, applied three machine learning algorithms to identify prognostic biomarkers, and performed drug prediction and molecular docking analyses to nominate therapeutic targets. ICD-related genes were predominantly overexpressed in ESCA, GBM, KIRC, LGG, PAAD, and STAD. RNA expression of most ICD-related genes was associated with poor prognosis, while DNA methylation of these genes showed significant survival correlations in LGG and UVM. Prognostic models were successfully established for 18 cancer types, revealing intrinsic immune regulatory mechanisms of ICD-related genes. Machine learning identified several key prognostic biomarkers across cancers, among which NT5E emerged as a predictive biomarker in head and neck squamous cell carcinoma (HNSC), mediating tumor–immune interactions through multiple ligand–receptor pairs. This study provides a comprehensive view of ICD-related genes across cancers, identifies NT5E as a potential biomarker in HNSC, and highlights novel targets for predicting immunotherapy response and improving clinical outcomes in cancer patients. Full article

The reaction of 4,4′-bipyridine (C₁₀H₈N₂) with the alkali metal pentacyanocyclopentadienides [Na{C₅(CN)₅}(MeOH)] and [KC₅(CN)₅] gives the coordination polymers [Na{C₅(CN)₅}(EtOH)(H₂O)(C₁₀H₈N₂)] (1) and [K{C₅(CN)₅}(H₂O)₂] • 2 (C₁₀H₈N₂) (2) after recrystallization from EtOH. Both compounds show octahedral coordination around the metal ion with a NaN₄O₂ and KN₂O₄ environment. The [C₅(CN)₅] acts as a 1,1-bridging ligand in 1 and a 1,2-bridging ligand in 2. The 4,4′-bipyridine acts as a N,N′-bridging ligand between dimeric [Na₂(EtOH)₂(H₂O)₂(µ-{C₅(CN)₅}₂] units, while it acts only as a guest molecule in the voids between polymeric [K(µ-H₂O)_4/2{µ-C₅(CN)₅}_2/2]_∞ chains. Both compounds employ multiple hydrogen bonds and π stacking to stabilize the crystalline structures. Full article

Background: The androgen receptor (AR) is a ligand-dependent transcription factor of the nuclear steroid receptor superfamily, implicated in the pathogenesis of various solid tumors. The AR gene, located on chromosome Xq11–12, is accompanied by several X-linked genes that modulate AR expression and function, including FLNA, UXT, and members of the melanoma antigen gene (MAGE) family (MAGEA1, MAGEA11, MAGEC1, MAGEC2). While the AR has been investigated in multiple tumor types, its role in adult-type diffuse gliomas remains largely unexplored. Here, we characterized AR protein expression and the promoter methylation status of the AR and associated regulatory genes in adult-type diffuse gliomas. Methods: A retrospective analysis was conducted on 50 patients with adult-type diffuse gliomas, including IDH-mutant gliomas (grades 2–4) and IDH-wildtype glioblastomas (GBMs), classified according to the 2021 WHO criteria. AR nuclear expression was assessed by immunohistochemistry (IHC). Methylation-specific PCR and quantitative DNA methylation analyses were employed to evaluate promoter methylation of the AR and selected co-regulatory genes. Results: AR nuclear positivity correlated significantly with male sex (p = 0.04) and higher tumor grade, with the highest expression in IDH-wildtype GBMs (p = 0.04). In IDH-mutant gliomas, AR immunoreactivity was more prevalent in astrocytomas than in 1p/19q codeleted oligodendrogliomas (p = 0.02). AR expression was associated with unmethylated MGMT promoter status (p = 0.02). DNA methylation analysis revealed AR gene hypomethylation in tumors displaying nuclear AR positivity and in IDH-wildtype GBMs (Kruskal–Wallis p < 0.05). Additionally, methylation patterns of AR co-regulators located on the X chromosome suggest epigenetic regulation of AR signaling in gliomas. Conclusions: The findings reveal distinct AR pathway activation patterns in adult-type diffuse gliomas, particularly IDH-wildtype GBMs, suggesting that further exploration of antiandrogen therapies is warranted. Full article

Integrating artificial intelligence (AI) with the Quantitative Structure-Activity Relationship (QSAR) has transformed modern drug discovery by empowering faster, more accurate, and scalable identification of therapeutic compounds. This review outlines the evolution from classical QSAR methods, such as multiple linear regression and partial least squares, to advanced machine learning and deep learning approaches, including graph neural networks and SMILES-based transformers. Molecular docking and molecular dynamics simulations are presented as cooperative tools that boost the mechanistic consideration and structural insight into the ligand-target interactions. Discussions on using PROTACs and targeted protein degradation, ADMET prediction, and public databases and cloud-based platforms to democratize access to computational modeling are well presented with priority. Challenges related to authentication, interpretability, regulatory standards, and ethical concerns are examined, along with emerging patterns in AI-driven drug development. This review is a guideline for using computational models and databases in explainable, data-rich and profound drug discovery pipelines. Full article

Adeno-associated virus (AAV) vectors are the preferred gene delivery tool in gene therapy owing to their safety, long-term gene expression, broad tissue tropism, and low immunogenicity. Affinity ligands that can bind multiple AAV serotypes endure harsh clean-in-place (CIP) conditions and are critical for industrial-scale purification. However, current ligands lack broad serotype recognition and adequate alkaline stability, which limits their reusability in large-scale manufacturing. In this study, we employed a competitive biopanning strategy to isolate a single-domain antibody (VHH) that simultaneously binds AAV2, AAV8, and AAV9. The VHH retained structural integrity and binding activity after exposure to 0.1 M NaOH, demonstrating robust alkaline stability. Structural modeling revealed that the VHH primarily recognizes the DE loop region of the VP3 capsid protein across the three serotypes, explaining its cross-serotype reactivity. Affinity chromatography using the VHH yielded infectious AAV particles, confirming its potential for downstream processing. This strategy provides a versatile platform for developing high-performance AAV affinity ligands and may be extended to other viral vector systems. Full article

Background and Objectives: Lupus nephritis (LN) is a major cause of mortality and morbidity in patients with systemic lupus erythematosus (SLE). Biomarkers derived from blood, urine, and multi-omics techniques are essential for enabling access to less invasive methods for LN evaluation and personalized precision medicine. Materials and Methods: The purpose of this work was to review the studies that addressed the potential role of urinary and serological biomarkers for the diagnosis, disease activity, response to treatment, and renal outcome of adult patients with LN, published over the past decade, and summarize their results with a particular emphasis being directed towards the available traditional tools. Results: Traditional biomarkers used for the diagnosis and surveillance of LN are proteinuria, urinary sediment, estimated glomerular filtration rate (eGFR), anti-double-stranded deoxyribonucleic acid (anti-dsDNA), anti-C1q, and serum complement levels. Anti-dsDNA, serum C3, and proteinuria are the conventional biomarkers with the strongest clinical evidence, with overall moderate ability in predicting LN from non-renal SLE, disease activity, renal flares, response to therapy, and prognosis. The last decade has brought significant progress in our understanding regarding the pathogenesis of LN and, consequently, several molecules, either alone or in combination panels, have emerged as potential novel biomarkers, some of them outperforming conventional biomarkers. Promising results have been suggested for urinary activated leukocyte cell adhesion molecule (ALCAM), soluble cluster of differentiation 163 (CD163), C-X-C motif chemokine ligand 10 (CXCL10), monocyte chemoattractant protein 1 (MCP-1), neutrophil gelatinase-associated lipocalin (NGAL), tumor necrosis factor-like weak inducer of apoptosis (TWEAK), and vascular cell adhesion molecule 1 (VCAM-1). Conclusions: Despite the intensive research of the last decade, no novel biomarker has entered clinical practice, and we continue to rely on traditional biomarkers to assess non-invasively LN and guide its treatment. Novel biomarkers should be validated in multiple longitudinal independent cohorts, compared with conventional biomarkers, and integrated with renal histology information in order to optimize the management of LN patients. Full article

Background/Objectives: Diffuse large B cell lymphoma (DLBCL) is a highly heterogeneous and aggressive lymphoma with a high incidence rate. Although modern therapeutic approaches have significantly improved patient survival rates, treatment relapse and drug resistance remain major clinical challenges. Programmed cell death (PCD) promotes tumorigenesis and regulates the tumor microenvironment (TME) and drug sensitivity. Exploring the application potential of PCD in DLBCL could pave the way for new treatment strategies for this malignancy. Methods: We systematically analyzed 13 types of PCD pathways and integrated transcriptomic and clinical data from 832 DLBCL patients (GSE10846, GSE11318, and GSE87371). A PCD-based prognostic signature, termed the Programmed Cell Death Score (PCDS), was constructed using 20 key PCD-related genes. Its clinical relevance was evaluated through survival analysis, drug response profiling, and tumor immune infiltration assessment using CIBERSORT, ESTIMATE, and ssGSEA algorithms. Results: The PCDS robustly stratified patients by survival and outperformed conventional clinical indicators such as age, stage, Eastern Cooperative Oncology Group (ECOG), and lactate dehydrogenase (LDH) in prognostic prediction. High-PCDS tumors were associated with immune suppression, characterized by reduced CD8⁺ T cell infiltration, elevated M2 macrophages, and increased programmed cell death protein 1 (PD-1)/programmed cell death ligand 1 (PD-L1) expression. Drug sensitivity analysis revealed that high-PCDS patients may benefit more from agents like sorafenib and fulvestrant, while low-PCDS patients responded better to NU7441. Functional validation using DLBCL cell lines and xenografts confirmed the oncogenic role of a representative gene (CTH) within the model. Conclusions: This study presents a novel prognostic scoring system derived from multiple PCD pathways that effectively stratifies DLBCL patients by risk and therapeutic responsiveness. Notably, the PCDS is closely associated with key immunological characteristics of the TME. These findings advance personalized treatment strategies and support clinically relevant decision-making in DLBCL. Full article

Parkinson’s disease is a neurodegenerative disorder characterized by the degeneration of dopaminergic neurons, resulting in multiple motor and cognitive impairments. Among the hypotheses proposed for its etiology, oxidative stress mediated by the enzyme monoamine oxidase B (MAO-B) stands out, as it is directly associated with dopamine metabolism. In this context, the search for molecules with potential antiparkinsonian activity and low toxicity, particularly those of natural origin, has been extensively investigated using computational approaches. In the present study, a pharmacophore-based virtual screening was carried out on molecules belonging to the alkaloid and flavonoid groups, followed by the evaluation of their pharmacokinetic, toxicological, and biological activity profiles, as well as ligand–receptor interaction analysis through molecular docking. The results indicated that palmatine, genistein, ZINC00597214, and ZINC72342127 exhibited superior performance compared to the other analyzed structures, considering all evaluated criteria. Therefore, this study, through in silico methodologies, demonstrated the antiparkinsonian potential of several chemical structures, attributable to their inhibitory activity on the MAO-B enzyme. Further experimental investigations, both in vitro and in vivo, are necessary to more comprehensively characterize the properties of these molecules, with the ultimate goal of developing new therapeutic strategies for the treatment of Parkinson’s disease. Full article

This work describes the synthesis and characterization of novel organometallic polymeric frameworks derived from lactone-based poly(benzofuran-co-arylacetic acid) (PBAAA) ligands complexed with 3d transition metal salts (Co²⁺, Cu²⁺, Zn²⁺). Two distinct synthetic approaches were investigated: conventional solution-based methods and mechanochemical ball milling. A comprehensive spectroscopic evaluation was performed utilizing FTIR, XRD, UV-Vis, and XPS techniques to detail the structural characteristics of the synthesized materials. The thermal assessments were conducted using TGA and thermal conductivity, demonstrating that the chosen synthesis method has a significant impact on the crystallinity, coordination environment, and thermal transport characteristics of the resultant complexes. Remarkably, using the mechanosynthesis, the resulting organometallic polymer materials exhibited enhanced chain ordering and improved thermal conductivity, with a value of 0.32 W/mK, almost double that of the starting polymer. A correlation was identified among thermal conductivity, metal ionic radius, coordination number, and the synthesis method utilized. XPS analysis revealed the presence of multiple oxidation states and varied electronic environments, particularly in copper complexes. These had a direct effect on how they behaved when heated. These results show that mechanochemical synthesis is a useful and long-lasting method to make complex organometallic polymers with thermal properties that can be changed. Full article

The proposed physiological roles of bile acids have expanded beyond the digestion of fats to encompass cell signaling via the activation of a variety of nuclear and plasma membrane receptors in multiple organ systems. The current in silico study was inspired by previous observations from our group and others that bile acids interact functionally with cardiac, pulmonary, and gastrointestinal muscarinic receptors and more recent work demonstrating allosteric binding of cholesterol, the parent molecule for bile acid synthesis, to M₁ muscarinic receptors (M₁R). Here, we computationally tested the hypothesis that bile acids can allosterically bind to M₁R and thereby modulate receptor activation. Utilizing de novo site identification by the ligand competitive saturation (SILCS) method, putative novel allosteric binding sites of bile acid targeting M₁R were identified. Molecular dynamics simulations were used to uncover the molecular details of the activation mechanism of M₁R due to agonist binding along with allosteric modulation of bile acids on M₁R activation. Allosteric binding of bile acids and their glycine and taurine conjugates to M₁R negatively impacts the activation process, findings consistent with recent reports that M₁R expression and activation inhibit colon cancer cell proliferation. Thus, bile acids may augment colon cancer risk by inhibiting the tumor suppressor actions of M₁R. When validated experimentally, these findings are anticipated to shed light on our understanding of how bile acids in the membrane microenvironment can allosterically modulate the function of M₁R and possibly other G protein-coupled receptors. Full article

Cancer remains a major global health concern, and thus, there is a growing demand for efficient and selective therapies with low systemic toxicity. Natural bioactive compounds have emerged as promising alternatives, and terpenoids have shown notable anticancer properties. They exert antiproliferative, proapoptotic, anti-invasive, and antimetastatic effects through the regulation of multiple molecular targets and signaling pathways, including modulation of apoptosis, suppression of angiogenesis, and inhibition of tumor-promoting inflammation. However, their clinical translation is constrained by poor aqueous solubility, low bioavailability, rapid systemic clearance, and inadequate tumor accumulation. Recent advances in nanotechnology offer strategies to overcome these limitations. Nanocarrier-based systems improve the solubility, stability, and pharmacokinetics of terpenoids, while enabling tumor-targeted delivery and controlled release. Various strategies, such as enhanced permeability and retention effect, ligand-mediated active targeting, and stimuli-responsive release have been used to achieve selective tumor accumulation and improved therapeutic outcomes. The purpose of this review is to provide a comprehensive evaluation of nanoformulated terpenoids in cancer with a special emphasis on their therapeutic applications and mechanisms of action. Preclinical studies demonstrate that nanocarrier-loaded terpenoids significantly increase bioavailability, enhance apoptosis, and suppress tumor angiogenesis compared with free terpenoids. The incorporation of artificial intelligence and machine learning further holds promise for the rational design of nanomedicines, accelerating their path toward clinical translation. Collectively, these developments position nanoformulated terpenoids as a powerful platform in precision oncology with strong potential for future application in cancer therapy. Full article

The coordination chemistry of a hydrazinylpyrazine-derived Schiff base ligand (L1), formed in situ from salicylaldehyde and 2-hydrazinopyrazine, with Fe(III) salts has been systematically investigated under varied synthetic conditions. Six discrete Fe(III) complexes (1a–1e and 2) were isolated and structurally characterised via single-crystal X-ray diffraction, revealing diverse coordination geometries ranging from five-coordinate pseudo-trigonal bipyramidal to six-coordinate pseudo-octahedral environments. The supramolecular architectures are governed by a rich interplay of non-covalent interactions, including hydrogen bonding, halogen bonding, and π–π stacking, which significantly influence the crystallisation pathways and final solid-state structures. Continuous shape measure (CShM) analysis highlights substantial geometric distortion in the bis-tridentate complexes, attributed to the steric and electronic constraints imposed by the ligand. Powder X-ray diffraction and infrared spectroscopy confirm the presence of multiple phases in bulk samples, underscoring the kinetic competition between crystallisation and coordination. The results demonstrate that supramolecular stabilisation of monoligated species can kinetically inhibit bis-ligation, with ligand excess and solvent polarity serving as key parameters to direct complex speciation. These findings provide insight into the delicate balance between coordination geometry, ligand strain, and supramolecular assembly in Fe(III) Schiff base complexes. Full article

Arsenic (As) is a toxic trace element with neurodevelopmental, carcinogenic, and other adverse effects. Meanwhile, selenium (Se) is an antioxidant trace element with essential physiological roles in humans. The preterm neonate is the most heavily transfused patient. The multiple blood transfusions could expose this vulnerable group to trace elements with variable effects. This study aimed to quantify As and Se in various blood products that were used in neonatal blood transfusions alongside an estimate of a dose per transfusion. In addition to exposure quantification, database mining and molecular docking analysis were performed to explore potential detoxification strategies. Samples from transfusion bags: N = 120; 30 samples of each type of blood product (plasma, platelets, packed RBCs (pRBCs), and whole blood “WB”) were analyzed for As and Se by using Inductively Coupled Plasma Mass Spectrometry (ICP-MS). The As and Se medians of all blood units were 0.6 and 74 μg/L, respectively. About 20% of donors have As levels above 1 μg/L. In addition, 74% of donors have Se levels less than 100 μg/L (the level of sub-optimal activity of the antioxidant enzyme glutathione peroxidase), and 60% of the donors have Se levels below the accepted minimum Se level (80 μg/L). The pRBCs were the units with the highest As and Se content. Meanwhile, WBs were the units with the highest dose per transfusion. Key methyl donors—folic acid, S-adenosylmethionine (SAM), and glutathione (GSH)—showed strong binding affinity to the active site of arsenite methyltransferase (AS3MT), a crucial enzyme in As metabolism. These ligands interacted with conserved catalytic residues such as ASN173, ASP115, and CYS92, suggesting a supportive role in enhancing As methylation and clearance. The present study highlights that neonates are exposed to As and Se via different blood product transfusions with high potential to increase As and decrease Se after transfusion. It is recommended to select donors and screen blood units with optimal Se levels and minimal As content for neonatal transfusions. The integration of in silico docking with exposure assessment adds mechanistic insight and highlights the potential for targeted nutritional interventions to reduce As toxicity in vulnerable neonatal populations. Full article